Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts.

Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.

Learn basic concepts of measurement and probability theory, data management, and research design

Discover basic statistical procedures, including correlation, the t-test, the chi-square and Fisher’s exact tests, and techniques for analyzing nonparametric data

Learn advanced techniques based on the general linear model, including ANOVA, ANCOVA, multiple linear regression, and logistic regression

Use and interpret statistics for business and quality improvement, medical and public health, and education and psychology

Communicate with statistics and critique statistical information presented by others

Sarah Boslaugh

Sarah Boslaugh holds a PhD in Research and Evaluation from the City University of New York and have been working as a statistical analyst for 15 years, in a variety of professional settings, including the New York City Board of Education, the Institutional Research Office of the City University of New York, Montefiore Medical Center, the Virginia Department of Social Services, Magellan Health Services, Washington University School of Medicine, and BJC HealthCare. She has taught statistics in several different contexts and currently teaches Intermediate Statistics at Washington University Medical School. She has published two previous books: An Intermediate Guide to SPSS Programming: Using Syntax for Data Management (SAGE Publications, 2004) and Secondary Data Sources for Public Health (forthcoming from Cambridge U. Press, 2007) and am currently editing the Encyclopedia of Epidemiology for SAGE Publications (forthcoming, 2007).

The animal on the cover of Statistics in aNutshell is a thornback crab, also known as a spiny spider crab(Maja squinado, Majabrachydactyla). Found in the northeast Atlantic Ocean and theMediterranean Sea, the thornback crab is the largest of the European crabs,with a carapace diameter of two to seven inches. It is easily identifiableby the two hornlike spikes between its eyes, and the six or so smallerspikes that extend from each side of its shell. The thornback’s body isreddish with pink, brown, or yellow markings, and its surface is alsocovered with small spikes, as the crab's name implies.Thornback crabs are occasionally found on the shore, but they preferdepths of 90 to 600 feet. They are solitary animals except during matingseason, when they form large breeding mounds. In years when their numbersare particularly abundant, they can be a source of frustration for lobsterfisherman as they infest the lobster pots. Thornbacks are themselves fishedfor their delicious claw meat.Male thornbacks are effective predators; their delicate-looking clawsare actually quite powerful and can open small mussels to feed on them.Their claws are also double-jointed, so although it is generally safe for aperson to hold crustaceans by each side of their shells, thornbacks are ableto reach over their backs to pinch the offender. Females have smaller, lessflexible claws and are thus more vulnerable to attack. To defend againsttheir predators—which include lobsters, wrasses, and cuttlefish—many speciesof spider crabs decorate their spiny shells with seaweed, sponges, oraquatic debris to better blend in against the seabed.The cover image is from Lydekker’s Library of NaturalHistory.

I wanted a book about statistics that I could use to quickly look up certain topics when I needed them.

And I got something else: When I first needed it, I wanted to make sure that I got the formula of the normal distribution right. Although the normal distribution is covered in detail including a probability table, the short formula is not mentioned (at least I didn't find it in my ebook version). I was not satisfied at all.

However, when reading the text and not using the book as formula-reference, this book is fascinating: The author precisely explains things in one sentence where I would have needed several paragraphs. It's really nice to read that book - I learned a lot, even about things I thought I knew very well.

To summarize: I don't think that this is the only book you'll need to have if you want to do statistics and it's no "reference" if you are looking for mathematical backgrounds but it helps a lot to _understand_ statistics. Is it possible to understand statistics without the complete underlying mathematics? Before reading this book I would have said "no". Now I say "maybe".

I have enjoyed reading this to-the-point statistics reference thanks to its sound organization, excellent communication style, and the detailed examples it provides. I am using this to refresh my memory on a variety of stats topics, and I have been pleasantly surprised at the robust content of this book. It will serve as a valuable member of any analytics professional's personal e-Library. Cheers.

This is a great book for those away from stats or new to stats. It is well written with a discussion of the topic and then an example of the topic applied. I like that the author covers mathematical symbols such as alpha, beta, theta, sigma, mean, etc.

I like this book, I purchased the first edition for a class, and it has been very helpful in my consulting practice. But I can't see much value in the 2nd edition; my view is that a new edition should contain something new, and not largely just correct errata. What about data mining? Analytics? So many new topics that could be included as new chapters but are sadly missing.

I bought this e-book (download) 2 years ago and have to disagree with the reviewer above. I use it to quickly review the method I'm intending to use. It's useful enough that I keep it on my desktop.

While it may be "simple", that allows the reader to find the material fast. It's a Nutshell book, not a textbook. As for errors, yes, there are some, but I have an errata sheet from O'Reilly which hits the major ones. Besides, it's easy to find them anyway.

My primary disappointments were: (1) too-skimpy coverage of cluster analysis. Two more pages would have *really* helped. K-means clustering is actively deceptive when you guess K wrong, and (2) In the medical section, nothing about receiver-operator curves (used in radiology).

If you want a "reminder" book, this works well ("oh, that's how that technique works" or "OK, now I'll go look up more details in the textbook"). If you want all the info at your fingertips, this book is not for you.

I think this is a good attempt to write an introductory statistics book, but some of the explanations leave much to be desired. For example, the first chapter reviews "types" or "levels" which I think most statisticians would refer to as "scales" of measurement. Error scores as shown as "+2" rather than as "-/+ 2". I think if the basics are not OK, then the book overall is questionable. Cronbach's alpha in Chapter 1? It should perhaps be titled "Statistics for Education Researchers" not a generic O'Reilly book (which is usually for IT readers).